Using Acoustic Sensor Technologies to Create a More Terrain Capable Unmanned Ground Vehicle

Authors:
Siddharth Odedra;Stephen D. Prior;Mehmet Karamanoglu;Mehmet Ali Erbil;Siu-Tsen Shen
Affiliations:
Department of Product Design and Engineering, School of Engineering and Information Sciences, Middlesex University, London, United Kingdom N14 4YZ;Department of Product Design and Engineering, School of Engineering and Information Sciences, Middlesex University, London, United Kingdom N14 4YZ;Department of Product Design and Engineering, School of Engineering and Information Sciences, Middlesex University, London, United Kingdom N14 4YZ;Department of Product Design and Engineering, School of Engineering and Information Sciences, Middlesex University, London, United Kingdom N14 4YZ;Department of Multimedia Design, National Formosa University, Hu-Wei, Taiwan 63208
Venue:
EPCE '09 Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009
Year:
2009

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Improving the mobility performance of autonomous unmanned ground vehicles by adding the ability to 'Sense/Feel' their local environment

ICVR'07 Proceedings of the 2nd international conference on Virtual reality

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Abstract

Unmanned Ground Vehicle's (UGV) have to cope with the most complex range of dynamic and variable obstacles and therefore need to be highly intelligent in order to cope with navigating in such a cluttered environment. When traversing over different terrains (whether it is a UGV or a commercial manned vehicle) different drive styles and configuration settings need to be selected in order to travel successfully over each terrain type. These settings are usually selected by a human operator in manned systems on what they assume the ground conditions to be, but how can an autonomous UGV `sense' these changes in terrain or ground conditions? This paper will investigate noncontact acoustic sensor technologies and how they can be used to detect different terrain types by listening to the interaction between the wheel and the terrain. The results can then be used to create a terrain classification list for the system so in future missions it can use the sensor technology to identify the terrain type it is trying to traverse, which creating a more autonomous and terrain capable vehicle. The technology would also benefit commercial driver assistive technologies.